Proceedings. AMIA Symposium最新文献

As the amount of data in public genomic databases grows, interoperability among them is becoming an increasingly critical feature. The ability for automated systems to mine and integrate data will be crucial to extracting knowledge from sources of data whose volume far exceeds the capabilities of human researchers. The currently dominant paradigm of presenting information as Web pages and using hyperlinks to describe relationships between pieces of information favors usability, but makes interoperability and automated data exchange more difficult. In this paper we describe how SNPper, a web-based system for the retrieval and analysis of Single Nucleotide Polymorphisms (SNPs), was augmented with a Remote Procedure Call interface, allowing client applications to query our program for SNP data and to receive the response as an XML document. Data represented in this form can be easily parsed by the requesting program, and thus reused for other applications. In this paper we describe the implementation of the interface and we show examples of its usage in a number of existing applications.

Physicians have many unmet information needs that arise in the course of patient care. Many clinical questions could potentially be answered by streamlined access to medical literature, textbooks, and clinical guidelines in the context of the electronic medical record. We designed and implemented SmartQuery, a prototype application to provide context-sensitive links from an electronic patient record to relevant medical knowledge sources, then performed a preliminary user evaluation. Our results suggest that such an application may be clinically useful, and provide some insight into problems and priorities for future development.

Bridging levels of scale and context are key problems for integrating Bio- and Health Informatics. Formal, logic-based ontologies using expressive formalisms are naturally "fractal" and provide new methods to support these aims. The basic notion of composition can be used to bridge scales; axioms can be used to carry implicit information; specific context markers can be included in definitions; and a hierarchy of semantic links can be used to represent subtle differences in point of view. Experience with OpenGALEN, the UK Drug Ontology and new experiments with the Gene Ontology and Foundational Model of Anatomy suggest that these are powerful tools provide practical solutions.

We have analyzed a publicly available dataset consisting of gene-expression measurements from 105 lung carcinomas joined with clinical parameters describing the age, smoking history, and survival statistics for the patients that the tumors originated in. Our aim was to demonstrate how the unsupervised analysis technique embodied in PathlinX allows researchers to quickly gain an intuition for the most significant relationships between heterogeneous data elements. A variety of metrics were evaluated empirically by their ability to distinguish biological signal in the data from random noise; this was accomplished by random permutation of the data rows followed by comprehensive pair-wise comparison of all experimental elements. Thresholds of significance were established based on the metric scores for the permuted data. Sub-threshold associations were then removed. The remaining associations were then grouped by a transitive closure process to generate undirected graphs of associations called PathlinX networks. We discuss the various features of each generated PathlinX network and demonstrate the ability of the technique to highlight biological features in large heterogeneous datasets.

The German language and in particular biomedical terms exhibit a rich and productive morphology. Beyond inflection and comparison forms frequently spelling variants, German - Greek/Latin synonyms and nominal compounds exist. For the English language, the SPECIALIST LEXICON, part of the UMLS project, covers a broad range of biomedical terms. In this paper we describe the database model and the functionality of the GERMAN SPECIALIST LEXICON, an ongoing project to develop a lexical resource for German-language medical terminology. Similar to the SPECIALIST LEXICON it is accompanied by tools for the recognition and generation of lexical variants, as well as by databases linking synonymous words, spelling variants, phrases and abbreviations.

At Columbia-Presbyterian Medical Center, free-text "Signout" notes are typed into the electronic record by clinicians for the purpose of cross-coverage. We plan to "unlock" information about adverse events contained in these notes in a subsequent project using Natural Language Processing (NLP). To better understand the requirements for parsing, Signout notes were compared to other common medical notes (ambulatory clinic notes and discharge summaries) on a series of quantitative metrics. They are shorter (mean length 59.25 words vs. 144.11 and 340.85 for ambulatory and discharge notes respectively) and use more abbreviations (26.88% vs. 20.07% and 3.57%). Despite being terser, Signout notes use less ambiguous abbreviations (8.34% vs. 9.09% and 18.02%). Differences were found using Relative Entropy and Squared Chi-square Distance in a novel fashion to compare these medical corpora. Signout notes appear to constitute a unique sublanguage of medicine. The implications for parsing free-text cross-coverage notes into coded medical data are discussed.

The American Board of Family Practice is developing a patient simulation program to evaluate diagnostic and management skills. The simulator must give temporally and physiologically reasonable answers to symptom questions such as "Have you been tired?" A three-step process generates symptom histories. In the first step, the simulator determines points in time where it should calculate instantaneous symptom status. In the second step, a Bayesian network implementing a roughly physiologic model of the symptom generates a value on a severity scale at each sampling time. Positive, zero, and negative values represent increased, normal, and decreased status, as applicable. The simulator plots these values over time. In the third step, another Bayesian network inspects this plot and reports how the symptom changed over time. This mechanism handles major trends, multiple and concurrent symptom causes, and gradually effective treatments. Other temporal insights, such as observations about short-term symptom relief, require complimentary mechanisms.

To address the problem of semantic inconsistencies between medical databases, semantic network representations can be utilized to automate the matching of medical concepts between the databases. The performance of automated concept matching was tested by creating semantic network representations for two laboratory databases, one from a pediatric hospital and the other from an oncology institute. The matching algorithms identified all equivalent concepts that were present in both databases, and did not leave any equivalent concepts unmatched. By automatically identifying semantically equivalent concepts, the Medical Information Acquisition and Transmission Enabler (MEDIATE) facilitates data exchange between heterogeneous systems because no pre-negotiation is required. Consequently, system scalability and stability is improved.

Digital or digitized biomedical images often have very high resolutions', which make them difficult or impossible to display on computer screens. Therefore, it is desirable to develop a multiresolution display method with which users can freely browse the contents of those high resolution images. In this paper, we present an improved wavelet-based progressive image display algorithm by stressing on the encoding and decoding process. The encoder, which dynamically determines levels of transform and partition of coefficients, is based on a modified Haar wavelet transform. The decoder retrieves the necessary data and reconstructs the requested region at a scale specified by the user. A prototype system, which enables virtually any size of images to be displayed progressively, has been implemented based on this algorithm. The system has low computational complexity for both encoding and decoding process.

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system.